I'm excited that the Google Brain team (g.co/brain) will have a decent presence at ICLR 2017 (http://www.iclr.cc), with 20 papers (including 4 papers chosen for oral presentation), plus an additional 4 papers in the workshop track. Of these, 9 of the papers have co-authors from our Brain Residency program (g.co/brainresidency), and another 8 have co-authors who were interns in our group. The Brain affiliated papers are below:

- Understanding deep learning requires rethinking generalization, by Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals, http://openreview.net/forum?id=Sy8gdB9xx (Intern co-author), Oral
- Neural Architecture Search with Reinforcement Learning, by Barret Zoph and Quoc Le, http://openreview.net/forum?id=r1Ue8Hcxg (Brain Resident co-author), Oral
- Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data, by Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, Kunal Talwar, http://openreview.net/forum?id=HkwoSDPgg, Oral
- Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic, by Shixiang (Shane) Gu, Timothy Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine, http://openreview.net/forum?id=SJ3rcZcxl (Intern co-author), Oral
- Adversarial Machine Learning at Scale, by Alexey Kurakin, Ian J. Goodfellow, Samy Bengio, http://openreview.net/forum?id=BJm4T4Kgx
- Density estimation using Real NVP, by Laurent Dinh, Jascha Sohl-Dickstein, Samy Bengio, http://openreview.net/forum?id=HkpbnH9lx (Intern co-author)
- Learning to Remember Rare Events, by Lukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio, http://openreview.net/forum?id=S1yTEt9ex (Brain Resident co-author)
- Categorical Reparameterization with Gumbel-Softmax, by Eric Jang, Shixiang (Shane) Gu, Ben Poole, http://openreview.net/forum?id=rkE3y85ee (Intern co-author)
- HyperNetworks, by David Ha, Andrew Dai, Quoc V. Le, http://openreview.net/forum?id=rkpACe1lx (Brain Resident co-author)
- Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer, by Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean, http://openreview.net/forum?id=B1ckMDqlg (Brain Resident co-author)
- Learning a Natural Language Interface with Neural Programmer, by Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei, http://openreview.net/forum?id=ry2YOrcge (Intern co-author)
- Deep Information Propagation, by Samuel Schoenholz, Justin Gilmer, Surya Ganguli, Jascha Sohl-Dickstein, http://openreview.net/forum?id=H1W1UN9gg (Brain Resident co-author)
- Decomposing Motion and Content for Natural Video Sequence Prediction, by Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee, http://openreview.net/forum?id=rkEFLFqee
- Capacity and Trainability in Recurrent Neural Networks, by Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo, http://openreview.net/pdf?id=BydARw9ex (Brain Resident co-author)
- Unrolled Generative Adversarial Networks, by Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein, http://104.155.136.4:3000/forum?id=BydrOIcle (Brain Resident co-author)
- A Learned Representation For Artistic Style, by Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur, http://openreview.net/forum?id=BJO-BuT1g (Intern co-author)
- Identity Matters in Deep Learning, by Moritz Hardt, Tengyu Ma, http://openreview.net/forum?id=ryxB0Rtxx
- Latent Sequence Decompositions, by William Chan, Yu Zhang, Quoc Le, Navdeep Jaitly, http://104.155.136.4:3000/forum?id=SyQq185lg (Intern co-author)
- Improving policy gradient by exploring under-appreciated rewards, by Ofir Nachum, Mohammad Norouzi, Dale Schuurmans, http://openreview.net/forum?id=ryT4pvqll (Brain Resident co-author)
- Adversarial Training Methods for Semi-Supervised Text Classification, by Takeru Miyato, Andrew M. Dai, Ian Goodfellow, https://openreview.net/forum?id=r1X3g2_xl
- Adversarial examples in the physical world, by Alexey Kurakin, Ian J. Goodfellow, Samy Bengio, http://openreview.net/forum?id=S1OufnIlx, Workshop
- Short and Deep: Sketching and Neural Networks, by Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar, http://openreview.net/forum?id=r1br_2Kge, Workshop
- Unsupervised Perceptual Rewards for Imitation Learning, by Pierre Sermanet, Kelvin Xu, Sergey Levine, http://openreview.net/pdf?id=Bkul3t9ee (Brain Resident co-author), Workshop
- Tuning Recurrent Neural Neworks with Reinforcement Learning, by Natasha Jaques, Shixiang (Shane) Gu, Richard E. Turner, Douglas Eck, http://openreview.net/forum?id=BJ8fyHceg, (Intern co-author), Workshop

You can find the full list of accepted papers at ICLR 2017 here:
https://openreview.net/group?id=ICLR.cc/2017/conference

Edit: Added intern identification to one of the papers
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